
"""simple docstring"""






import gc
import unittest

import numpy as np
import torch

from diffusers import AutoencoderKL, DDIMScheduler, DiTPipeline, DPMSolverMultistepScheduler, TransformeraDModel
from diffusers.utils import is_xformers_available, load_numpy, slow, torch_device
from diffusers.utils.testing_utils import enable_full_determinism, require_torch_gpu

from ..pipeline_params import (
    CLASS_CONDITIONED_IMAGE_GENERATION_BATCH_PARAMS,
    CLASS_CONDITIONED_IMAGE_GENERATION_PARAMS,
)
from ..test_pipelines_common import PipelineTesterMixin


enable_full_determinism()



class 			lowercase					( lowercase__   ,unittest.TestCase		):
			lowercase        =     DiTPipeline
			lowercase        =     CLASS_CONDITIONED_IMAGE_GENERATION_PARAMS
			lowercase        =     PipelineTesterMixin.required_optional_params - {
			    '''latents''',
			    '''num_images_per_prompt''',
			    '''callback''',
			    '''callback_steps''',
			}
			lowercase        =     CLASS_CONDITIONED_IMAGE_GENERATION_BATCH_PARAMS
			lowercase        =     False






			def 					UpperCAmelCase							(self  :	List[str]			)       ->	str:





				"""simple docstring"""


				torch.manual_seed(0			)
				lowerCAmelCase												=  TransformeraDModel(
				    sample_size=16      ,num_layers=2      ,patch_size=4      ,attention_head_dim=8      ,num_attention_heads=2      ,in_channels=4      ,out_channels=8      ,attention_bias=SCREAMING_SNAKE_CASE_      ,activation_fn='''gelu-approximate'''      ,num_embeds_ada_norm=1_000      ,norm_type='''ada_norm_zero'''      ,norm_elementwise_affine=SCREAMING_SNAKE_CASE_      ,)
				lowerCAmelCase												=  AutoencoderKL()
				lowerCAmelCase												=  DDIMScheduler()
				lowerCAmelCase												=  {'''transformer''': transformer.eval(), '''vae''': vae.eval(), '''scheduler''': scheduler}
				return components






			def 					UpperCAmelCase							(self  :	str      ,SCREAMING_SNAKE_CASE_  :	int      ,SCREAMING_SNAKE_CASE_  :	str=0			)       ->	Tuple:





				"""simple docstring"""


				if str(SCREAMING_SNAKE_CASE_			).startswith('''mps'''			):
					lowerCAmelCase												=  torch.manual_seed(SCREAMING_SNAKE_CASE_			)
				else:
					lowerCAmelCase												=  torch.Generator(device=SCREAMING_SNAKE_CASE_			).manual_seed(SCREAMING_SNAKE_CASE_			)
				lowerCAmelCase												=  {
				    '''class_labels''': [1],
				    '''generator''': generator,
				    '''num_inference_steps''': 2,
				    '''output_type''': '''numpy''',
				}
				return inputs






			def 					UpperCAmelCase							(self  :	List[str]			)       ->	Union[str, Any]:





				"""simple docstring"""


				lowerCAmelCase												=  '''cpu'''

				lowerCAmelCase												=  self.get_dummy_components()
				lowerCAmelCase												=  self.pipeline_class(**SCREAMING_SNAKE_CASE_			)
				pipe.to(SCREAMING_SNAKE_CASE_			)
				pipe.set_progress_bar_config(disable=SCREAMING_SNAKE_CASE_			)

				lowerCAmelCase												=  self.get_dummy_inputs(SCREAMING_SNAKE_CASE_			)
				lowerCAmelCase												=  pipe(**SCREAMING_SNAKE_CASE_			).images
				lowerCAmelCase												=  image[0, -3:, -3:, -1]

				self.assertEqual(image.shape      ,(1, 16, 16, 3)			)
				lowerCAmelCase												=  np.array([0.29_46, 0.66_01, 0.43_29, 0.32_96, 0.41_44, 0.53_19, 0.72_73, 0.50_13, 0.44_57]			)
				lowerCAmelCase												=  np.abs(image_slice.flatten() - expected_slice			).max()
				self.assertLessEqual(SCREAMING_SNAKE_CASE_      ,1e-3			)






			def 					UpperCAmelCase							(self  :	Optional[int]			)       ->	int:





				"""simple docstring"""


				self._test_inference_batch_single_identical(relax_max_difference=SCREAMING_SNAKE_CASE_      ,expected_max_diff=1e-3			)






			@unittest.skipIf(
			    torch_device != '''cuda''' or not is_xformers_available()      ,reason='''XFormers attention is only available with CUDA and `xformers` installed'''      ,)
			def 					UpperCAmelCase							(self  :	Union[str, Any]			)       ->	Union[str, Any]:





				"""simple docstring"""


				self._test_xformers_attention_forwardGenerator_pass(expected_max_diff=1e-3			)





@require_torch_gpu
@slow
class 			lowercase					( unittest.TestCase		):






			def 					UpperCAmelCase							(self  :	Union[str, Any]			)       ->	Dict:





				"""simple docstring"""


				super().tearDown()
				gc.collect()
				torch.cuda.empty_cache()






			def 					UpperCAmelCase							(self  :	Dict			)       ->	Optional[int]:





				"""simple docstring"""


				lowerCAmelCase												=  torch.manual_seed(0			)

				lowerCAmelCase												=  DiTPipeline.from_pretrained('''facebook/DiT-XL-2-256'''			)
				pipe.to('''cuda'''			)

				lowerCAmelCase												=  ['''vase''', '''umbrella''', '''white shark''', '''white wolf''']
				lowerCAmelCase												=  pipe.get_label_ids(SCREAMING_SNAKE_CASE_			)

				lowerCAmelCase												=  pipe(SCREAMING_SNAKE_CASE_      ,generator=SCREAMING_SNAKE_CASE_      ,num_inference_steps=40      ,output_type='''np'''			).images

				for word, image in zip(SCREAMING_SNAKE_CASE_      ,SCREAMING_SNAKE_CASE_			):
					lowerCAmelCase												=  load_numpy(
					    F"""https://huggingface.co/datasets/hf-internal-testing/diffusers-images/resolve/main/dit/{word}.npy"""			)
					assert np.abs((expected_image - image).max()			) < 1e-2






			def 					UpperCAmelCase							(self  :	Any			)       ->	int:





				"""simple docstring"""


				lowerCAmelCase												=  DiTPipeline.from_pretrained('''facebook/DiT-XL-2-512'''			)
				lowerCAmelCase												=  DPMSolverMultistepScheduler.from_config(pipe.scheduler.config			)
				pipe.to('''cuda'''			)

				lowerCAmelCase												=  ['''vase''', '''umbrella''']
				lowerCAmelCase												=  pipe.get_label_ids(SCREAMING_SNAKE_CASE_			)

				lowerCAmelCase												=  torch.manual_seed(0			)
				lowerCAmelCase												=  pipe(SCREAMING_SNAKE_CASE_      ,generator=SCREAMING_SNAKE_CASE_      ,num_inference_steps=25      ,output_type='''np'''			).images

				for word, image in zip(SCREAMING_SNAKE_CASE_      ,SCREAMING_SNAKE_CASE_			):
					lowerCAmelCase												=  load_numpy(
					    '''https://huggingface.co/datasets/hf-internal-testing/diffusers-images/resolve/main'''
					    F"""/dit/{word}_512.npy"""			)

					assert np.abs((expected_image - image).max()			) < 1e-1




"""simple docstring"""






import warnings
from collections import OrderedDict
from typing import Mapping

from packaging import version

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging


UpperCAmelCase        =				logging.get_logger(__name__)

UpperCAmelCase        =				{
    """nvidia/segformer-b0-finetuned-ade-512-512""": (
        """https://huggingface.co/nvidia/segformer-b0-finetuned-ade-512-512/resolve/main/config.json"""
    ),
    # See all SegFormer models at https://huggingface.co/models?filter=segformer
}



class 			lowercase					( lowercase__		):
			lowercase        =     '''segformer'''






			def __init__(self  :	str      ,SCREAMING_SNAKE_CASE_  :	Optional[Any]=3      ,SCREAMING_SNAKE_CASE_  :	List[str]=4      ,SCREAMING_SNAKE_CASE_  :	Union[str, Any]=[2, 2, 2, 2]      ,SCREAMING_SNAKE_CASE_  :	List[str]=[8, 4, 2, 1]      ,SCREAMING_SNAKE_CASE_  :	int=[32, 64, 160, 256]      ,SCREAMING_SNAKE_CASE_  :	Optional[Any]=[7, 3, 3, 3]      ,SCREAMING_SNAKE_CASE_  :	Union[str, Any]=[4, 2, 2, 2]      ,SCREAMING_SNAKE_CASE_  :	List[Any]=[1, 2, 5, 8]      ,SCREAMING_SNAKE_CASE_  :	Dict=[4, 4, 4, 4]      ,SCREAMING_SNAKE_CASE_  :	Optional[int]="gelu"      ,SCREAMING_SNAKE_CASE_  :	Optional[Any]=0.0      ,SCREAMING_SNAKE_CASE_  :	Union[str, Any]=0.0      ,SCREAMING_SNAKE_CASE_  :	List[str]=0.1      ,SCREAMING_SNAKE_CASE_  :	List[Any]=0.02      ,SCREAMING_SNAKE_CASE_  :	str=0.1      ,SCREAMING_SNAKE_CASE_  :	Dict=1e-6      ,SCREAMING_SNAKE_CASE_  :	List[str]=256      ,SCREAMING_SNAKE_CASE_  :	List[str]=255      ,**SCREAMING_SNAKE_CASE_  :	Tuple      ,)       ->	int:





				"""simple docstring"""


				super().__init__(**SCREAMING_SNAKE_CASE_			)

				if "reshape_last_stage" in kwargs and kwargs["reshape_last_stage"] is False:
					warnings.warn(
					    '''Reshape_last_stage is set to False in this config. This argument is deprecated and will soon be'''
					    ''' removed, as the behaviour will default to that of reshape_last_stage = True.'''      ,SCREAMING_SNAKE_CASE_      ,)

				lowerCAmelCase												=  num_channels
				lowerCAmelCase												=  num_encoder_blocks
				lowerCAmelCase												=  depths
				lowerCAmelCase												=  sr_ratios
				lowerCAmelCase												=  hidden_sizes
				lowerCAmelCase												=  patch_sizes
				lowerCAmelCase												=  strides
				lowerCAmelCase												=  mlp_ratios
				lowerCAmelCase												=  num_attention_heads
				lowerCAmelCase												=  hidden_act
				lowerCAmelCase												=  hidden_dropout_prob
				lowerCAmelCase												=  attention_probs_dropout_prob
				lowerCAmelCase												=  classifier_dropout_prob
				lowerCAmelCase												=  initializer_range
				lowerCAmelCase												=  drop_path_rate
				lowerCAmelCase												=  layer_norm_eps
				lowerCAmelCase												=  decoder_hidden_size
				lowerCAmelCase												=  kwargs.get('''reshape_last_stage'''      ,SCREAMING_SNAKE_CASE_			)
				lowerCAmelCase												=  semantic_loss_ignore_index





class 			lowercase					( lowercase__		):
			lowercase        =     version.parse('''1.11'''		)






			@property
			def 					UpperCAmelCase							(self  :	Union[str, Any]			)       ->	Mapping[str, Mapping[int, str]]:





				"""simple docstring"""


				return OrderedDict(
				    [
				        ('''pixel_values''', {0: '''batch''', 1: '''num_channels''', 2: '''height''', 3: '''width'''}),
				    ]			)






			@property
			def 					UpperCAmelCase							(self  :	str			)       ->	float:





				"""simple docstring"""


				return 1e-4






			@property
			def 					UpperCAmelCase							(self  :	Dict			)       ->	int:





				"""simple docstring"""


				return 12


